_a_t_a_c_

_e_n_c_o_d_e___a_t_a_c_

Pipeline version: v1

Report generated at 2019-06-24 04:12:53

Paired-end: [True, True, True]

Pipeline type: ATAC-Seq

Genome: GRCh38_no_alt_analysis_set_GCA_000001405.15.fasta.gz]

Peak caller: MACS2

Alignment

Flagstat (raw BAM)

Marking duplicates (filtered BAM)

Library complexity (filtered non-mito BAM)

Flagstat (filtered/deduped BAM)

Filtered and duplicates removed

Peak calling

IDR (Irreproducible Discovery Rate) plots

Reproducibility QC and peak detection statistics

Enrichment

Fraction of reads in overlapping peaks

Fraction of reads in IDR peaks

ATAQC

Summary table

Replicate 1

Sample Information

Summary

Note that all these read counts are determined using 'samtools view' - as such,
these are all reads found in the file, whether one end of a pair or a single
end read. In other words, if your file is paired end, then you should divide
these counts by two. Each step follows the previous step; for example, the
duplicate reads were removed after reads were removed for low mapping quality.

This bar chart also shows the filtering process and where the reads were lost
over the process. Note that each step is sequential - as such, there may
have been more mitochondrial reads which were already filtered because of
high duplication or low mapping quality. Note that all these read counts are
determined using 'samtools view' - as such, these are all reads found in
the file, whether one end of a pair or a single end read. In other words,
if your file is paired end, then you should divide these counts by two.

Alignment statistics

Bowtie alignment log

31605408 reads; of these:
  31605408 (100.00%) were paired; of these:
    2231425 (7.06%) aligned concordantly 0 times
    8744837 (27.67%) aligned concordantly exactly 1 time
    20629146 (65.27%) aligned concordantly >1 times
    ----
    2231425 pairs aligned concordantly 0 times; of these:
      661651 (29.65%) aligned discordantly 1 time
    ----
    1569774 pairs aligned 0 times concordantly or discordantly; of these:
      3139548 mates make up the pairs; of these:
        1055949 (33.63%) aligned 0 times
        108756 (3.46%) aligned exactly 1 time
        1974843 (62.90%) aligned >1 times
98.33% overall alignment rate

  

Samtools flagstat

167967377 + 0 in total (QC-passed reads + QC-failed reads)
104756561 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
166911428 + 0 mapped (99.37%:-nan%)
63210816 + 0 paired in sequencing
31605408 + 0 read1
31605408 + 0 read2
58747966 + 0 properly paired (92.94%:-nan%)
62032300 + 0 with itself and mate mapped
122567 + 0 singletons (0.19%:-nan%)
425130 + 0 with mate mapped to a different chr
42360 + 0 with mate mapped to a different chr (mapQ>=5)

  

Note that the flagstat command counts alignments, not reads. please 
use the read counts table to get accurate counts of reads at each
stage of the pipeline.

Filtering statistics

Mapping quality refers to the quality of the read being aligned to that
particular location in the genome. A standard quality score is > 30.
Duplications are often due to PCR duplication rather than two unique reads
mapping to the same location. High duplication is an indication of poor
libraries. Mitochondrial reads are often high in chromatin accessibility
assays because the mitochondrial genome is very open. A high mitochondrial
fraction is an indication of poor libraries. Based on prior experience, a
final read fraction above 0.70 is a good library.
  

Library complexity statistics

ENCODE library complexity metrics

The non-redundant fraction (NRF) is the fraction of non-redundant mapped reads
in a dataset; it is the ratio between the number of positions in the genome
that uniquely mapped reads map to and the total number of uniquely mappable
reads. The NRF should be > 0.8. The PBC1 is the ratio of genomic locations
with EXACTLY one read pair over the genomic locations with AT LEAST one read
pair. PBC1 is the primary measure, and the PBC1 should be close to 1.
Provisionally 0-0.5 is severe bottlenecking, 0.5-0.8 is moderate bottlenecking,
0.8-0.9 is mild bottlenecking, and 0.9-1.0 is no bottlenecking. The PBC2 is
the ratio of genomic locations with EXACTLY one read pair over the genomic
locations with EXACTLY two read pairs. The PBC2 should be significantly
greater than 1.

Picard EstimateLibraryComplexity

Yield prediction

Preseq performs a yield prediction by subsampling the reads, calculating the
number of distinct reads, and then extrapolating out to see where the
expected number of distinct reads no longer increases. The confidence interval
gives a gauge as to the validity of the yield predictions.

Fragment length statistics

Open chromatin assays show distinct fragment length enrichments, as the cut
sites are only in open chromatin and not in nucleosomes. As such, peaks
representing different n-nucleosomal (ex mono-nucleosomal, di-nucleosomal)
fragment lengths will arise. Good libraries will show these peaks in a
fragment length distribution and will show specific peak ratios.

Peak statistics

Naive overlap peak file statistics

IDR peak file statistics

For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks
for a specific cell type.

Sequence quality metrics

GC bias

Open chromatin assays are known to have significant GC bias. Please take this
into consideration as necessary.

Replicate 2

Sample Information

Summary

Note that all these read counts are determined using 'samtools view' - as such,
these are all reads found in the file, whether one end of a pair or a single
end read. In other words, if your file is paired end, then you should divide
these counts by two. Each step follows the previous step; for example, the
duplicate reads were removed after reads were removed for low mapping quality.

This bar chart also shows the filtering process and where the reads were lost
over the process. Note that each step is sequential - as such, there may
have been more mitochondrial reads which were already filtered because of
high duplication or low mapping quality. Note that all these read counts are
determined using 'samtools view' - as such, these are all reads found in
the file, whether one end of a pair or a single end read. In other words,
if your file is paired end, then you should divide these counts by two.

Alignment statistics

Bowtie alignment log

39069894 reads; of these:
  39069894 (100.00%) were paired; of these:
    2769616 (7.09%) aligned concordantly 0 times
    9999602 (25.59%) aligned concordantly exactly 1 time
    26300676 (67.32%) aligned concordantly >1 times
    ----
    2769616 pairs aligned concordantly 0 times; of these:
      716720 (25.88%) aligned discordantly 1 time
    ----
    2052896 pairs aligned 0 times concordantly or discordantly; of these:
      4105792 mates make up the pairs; of these:
        1552341 (37.81%) aligned 0 times
        116305 (2.83%) aligned exactly 1 time
        2437146 (59.36%) aligned >1 times
98.01% overall alignment rate

  

Samtools flagstat

211883832 + 0 in total (QC-passed reads + QC-failed reads)
133744044 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
210331491 + 0 mapped (99.27%:-nan%)
78139788 + 0 paired in sequencing
39069894 + 0 read1
39069894 + 0 read2
72600556 + 0 properly paired (92.91%:-nan%)
76479896 + 0 with itself and mate mapped
107551 + 0 singletons (0.14%:-nan%)
529216 + 0 with mate mapped to a different chr
49955 + 0 with mate mapped to a different chr (mapQ>=5)

  

Note that the flagstat command counts alignments, not reads. please 
use the read counts table to get accurate counts of reads at each
stage of the pipeline.

Filtering statistics

Mapping quality refers to the quality of the read being aligned to that
particular location in the genome. A standard quality score is > 30.
Duplications are often due to PCR duplication rather than two unique reads
mapping to the same location. High duplication is an indication of poor
libraries. Mitochondrial reads are often high in chromatin accessibility
assays because the mitochondrial genome is very open. A high mitochondrial
fraction is an indication of poor libraries. Based on prior experience, a
final read fraction above 0.70 is a good library.
  

Library complexity statistics

ENCODE library complexity metrics

The non-redundant fraction (NRF) is the fraction of non-redundant mapped reads
in a dataset; it is the ratio between the number of positions in the genome
that uniquely mapped reads map to and the total number of uniquely mappable
reads. The NRF should be > 0.8. The PBC1 is the ratio of genomic locations
with EXACTLY one read pair over the genomic locations with AT LEAST one read
pair. PBC1 is the primary measure, and the PBC1 should be close to 1.
Provisionally 0-0.5 is severe bottlenecking, 0.5-0.8 is moderate bottlenecking,
0.8-0.9 is mild bottlenecking, and 0.9-1.0 is no bottlenecking. The PBC2 is
the ratio of genomic locations with EXACTLY one read pair over the genomic
locations with EXACTLY two read pairs. The PBC2 should be significantly
greater than 1.

Picard EstimateLibraryComplexity

Yield prediction

Preseq performs a yield prediction by subsampling the reads, calculating the
number of distinct reads, and then extrapolating out to see where the
expected number of distinct reads no longer increases. The confidence interval
gives a gauge as to the validity of the yield predictions.

Fragment length statistics

Open chromatin assays show distinct fragment length enrichments, as the cut
sites are only in open chromatin and not in nucleosomes. As such, peaks
representing different n-nucleosomal (ex mono-nucleosomal, di-nucleosomal)
fragment lengths will arise. Good libraries will show these peaks in a
fragment length distribution and will show specific peak ratios.

Peak statistics

Naive overlap peak file statistics

IDR peak file statistics

For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks
for a specific cell type.

Sequence quality metrics

GC bias

Open chromatin assays are known to have significant GC bias. Please take this
into consideration as necessary.

Replicate 3

Sample Information

Summary

Note that all these read counts are determined using 'samtools view' - as such,
these are all reads found in the file, whether one end of a pair or a single
end read. In other words, if your file is paired end, then you should divide
these counts by two. Each step follows the previous step; for example, the
duplicate reads were removed after reads were removed for low mapping quality.

This bar chart also shows the filtering process and where the reads were lost
over the process. Note that each step is sequential - as such, there may
have been more mitochondrial reads which were already filtered because of
high duplication or low mapping quality. Note that all these read counts are
determined using 'samtools view' - as such, these are all reads found in
the file, whether one end of a pair or a single end read. In other words,
if your file is paired end, then you should divide these counts by two.

Alignment statistics

Bowtie alignment log

38415776 reads; of these:
  38415776 (100.00%) were paired; of these:
    2833839 (7.38%) aligned concordantly 0 times
    10478898 (27.28%) aligned concordantly exactly 1 time
    25103039 (65.35%) aligned concordantly >1 times
    ----
    2833839 pairs aligned concordantly 0 times; of these:
      739480 (26.09%) aligned discordantly 1 time
    ----
    2094359 pairs aligned 0 times concordantly or discordantly; of these:
      4188718 mates make up the pairs; of these:
        1709286 (40.81%) aligned 0 times
        126334 (3.02%) aligned exactly 1 time
        2353098 (56.18%) aligned >1 times
97.78% overall alignment rate

  

Samtools flagstat

204502326 + 0 in total (QC-passed reads + QC-failed reads)
127670774 + 0 secondary
0 + 0 supplementary
0 + 0 duplicates
202793040 + 0 mapped (99.16%:-nan%)
76831552 + 0 paired in sequencing
38415776 + 0 read1
38415776 + 0 read2
71163874 + 0 properly paired (92.62%:-nan%)
75003762 + 0 with itself and mate mapped
118504 + 0 singletons (0.15%:-nan%)
520554 + 0 with mate mapped to a different chr
57048 + 0 with mate mapped to a different chr (mapQ>=5)

  

Note that the flagstat command counts alignments, not reads. please 
use the read counts table to get accurate counts of reads at each
stage of the pipeline.

Filtering statistics

Mapping quality refers to the quality of the read being aligned to that
particular location in the genome. A standard quality score is > 30.
Duplications are often due to PCR duplication rather than two unique reads
mapping to the same location. High duplication is an indication of poor
libraries. Mitochondrial reads are often high in chromatin accessibility
assays because the mitochondrial genome is very open. A high mitochondrial
fraction is an indication of poor libraries. Based on prior experience, a
final read fraction above 0.70 is a good library.
  

Library complexity statistics

ENCODE library complexity metrics

The non-redundant fraction (NRF) is the fraction of non-redundant mapped reads
in a dataset; it is the ratio between the number of positions in the genome
that uniquely mapped reads map to and the total number of uniquely mappable
reads. The NRF should be > 0.8. The PBC1 is the ratio of genomic locations
with EXACTLY one read pair over the genomic locations with AT LEAST one read
pair. PBC1 is the primary measure, and the PBC1 should be close to 1.
Provisionally 0-0.5 is severe bottlenecking, 0.5-0.8 is moderate bottlenecking,
0.8-0.9 is mild bottlenecking, and 0.9-1.0 is no bottlenecking. The PBC2 is
the ratio of genomic locations with EXACTLY one read pair over the genomic
locations with EXACTLY two read pairs. The PBC2 should be significantly
greater than 1.

Picard EstimateLibraryComplexity

Yield prediction

Preseq performs a yield prediction by subsampling the reads, calculating the
number of distinct reads, and then extrapolating out to see where the
expected number of distinct reads no longer increases. The confidence interval
gives a gauge as to the validity of the yield predictions.

Fragment length statistics

Open chromatin assays show distinct fragment length enrichments, as the cut
sites are only in open chromatin and not in nucleosomes. As such, peaks
representing different n-nucleosomal (ex mono-nucleosomal, di-nucleosomal)
fragment lengths will arise. Good libraries will show these peaks in a
fragment length distribution and will show specific peak ratios.

Peak statistics

Naive overlap peak file statistics

IDR peak file statistics

For a good ATAC-seq experiment in human, you expect to get 100k-200k peaks
for a specific cell type.

Sequence quality metrics

GC bias

Open chromatin assays are known to have significant GC bias. Please take this
into consideration as necessary.